胃癌（GC）是一种多方面的胃肠道恶性肿瘤，是全球癌症相关死亡的第四大常见原因。作为 ATP 结合盒 (ABC) 家族的一员，与抗原加工相关的转运蛋白 1 (TAP1) 对于将抗原肽从细胞质转运至内质网腔并随后将其加载到主要组织相容性复合物 (MHC) 上至关重要。 ) I 类分子。最近的研究已经确定了 TAP1 在通过重塑肿瘤微环境 (TME) 和协调免疫浸润来维持肿瘤存活和促进免疫逃避方面的生物学意义。该研究旨在阐明 TAP1 表达与免疫学特征的关联，并试图利用 TAP1 作为反映炎症 TME 和免疫治疗反应的生物标志物的价值。RNA 测序图谱和临床注释来自癌症基因组图谱-胃腺癌 (TCGA-STAD) 队列和基因表达综合 (GEO) 门户。使用 limma 包进行预处理。加权基因共表达网络分析 (WGCNA) 用于根据相关模式识别基因模块和 TAP1 共表达基因 (CEG)。共识聚类和轮廓分析确定了 TAP1 相关组的最佳数量。使用 pamr 包对基因表达谱进行整合和分类。使用表达数据（ESTIMATE）算法和单样本基因集富集分析（ssGSEA）估计恶性肿瘤中的STromal和免疫细胞来评估免疫学特征。使用limma包进行差异表达分析。进行了基因本体论（GO）和京都基因和基因组百科全书（KEGG）途径富集分析。使用 Seurat 工具包分析单细胞 RNA 测序 (scRNA-seq) 数据集来表征细胞类型。在这项研究中，在表现出各种临床病理特征的患者中没有观察到 TAP1 表达的显着差异，表明 TAP1 表达并非分子特异性亚型。随后的分析揭示了 TAP1 与多种免疫学特征之间的正相关性，包括免疫调节剂、肿瘤浸润免疫细胞以及多个数据集中的免疫检查点。此外，在 GC 免疫治疗队列中，TAP1 高表达的个体表现出治疗后实现完全缓解 (CR) 的可能性增加，表明对免疫治疗的敏感性更高。在临床队列中，GC 患者中 TAP1 过度表达与 CD8 呈正相关。TAP1 似乎与发炎的 TME 相关，可作为辨别免疫属性和衡量 GC 免疫治疗反应的前瞻性生物标志物，特别是在识别免疫反应性肿瘤方面。2024 杂志胃肠肿瘤学。版权所有。

Gastric cancer (GC), a multifaceted gastrointestinal malignancy, is the fourth most prevalent contributor to cancer-related fatalities globally. As a member of the ATP-binding cassette (ABC) family, transporter associated with antigen processing 1 (TAP1) is crucial for conveying antigen peptides from the cytoplasm to the lumen of the endoplasmic reticulum and subsequently loading them onto the major histocompatibility complex (MHC) class I molecules. Recent studies have established the biological significance of TAP1 in upholding tumor survival and facilitating immune evasion by remodeling the tumor microenvironment (TME) and orchestrating immune infiltration. The study was conducted to elucidate the association of TAP1 expression with immunological characteristics, and sought to exploit the value of TAP1 as a biomarker reflecting the inflamed TME and immunotherapeutic response.RNA-sequencing profiles and clinical annotations were obtained from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort and Gene Expression Omnibus (GEO) portal. Preprocessing was conducting using the limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules and TAP1 co-expressed genes (CEGs) based on correlation patterns. Consensus clustering and silhouette analysis determined the optimal number of TAP1-related groups. Gene expression profiles were integrated and classified using the pamr package. The Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate immunological characteristics. Differential expression analysis was conducted using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Single-cell RNA sequencing (scRNA-seq) datasets were analyzed using the Seurat toolkit to characterize cell types.Within this investigation, no significant differences in TAP1 expression were observed among patients exhibiting various clinicopathological features, indicating that TAP1 expression was not specific to molecular subtypes. Subsequent analysis revealed a positive correlation between TAP1 and diverse immunological traits, encompassing immunomodulators, tumor-infiltrating immune cells, as well as immune checkpoints across multiple datasets. Besides, within a GC immunotherapy cohort, individuals displaying high TAP1 expression demonstrated an increased likelihood of achieving complete remission (CR) post-treatment, suggesting heightened sensitivity to immunotherapy. In the clinical cohort, TAP1 overexpression in GC patients was positively correlated with CD8.TAP1 appears linked to an inflamed TME and serves as a prospective biomarker for discerning immunological attributes and gauging immunotherapeutic responses in GC, particularly in identifying immune-reactive tumors.2024 Journal of Gastrointestinal Oncology. All rights reserved.